Google Generative AI Provider

The Google Generative AI provider contains language model support for the Google Generative AI APIs.

Setup

The Google provider is available in the @ai-sdk/google module. You can install it with

pnpm install @ai-sdk/google

Provider Instance

You can import the default provider instance google from @ai-sdk/google:

import { google } from '@ai-sdk/google';

If you need a customized setup, you can import createGoogleGenerativeAI from @ai-sdk/google and create a provider instance with your settings:

import { createGoogleGenerativeAI } from '@ai-sdk/google';

const google = createGoogleGenerativeAI({
  // custom settings
});

You can use the following optional settings to customize the Google Generative AI provider instance:

• baseURL string

  Use a different URL prefix for API calls, e.g. to use proxy servers. The default prefix is https://generativelanguage.googleapis.com/v1beta.

• apiKey string

  API key that is being send using the x-goog-api-key header. It defaults to the GOOGLE_GENERATIVE_AI_API_KEY environment variable.

• headers Record<string,string>

  Custom headers to include in the requests.

• fetch (input: RequestInfo, init?: RequestInit) => Promise<Response>

  Custom fetch implementation. Defaults to the global fetch function. You can use it as a middleware to intercept requests, or to provide a custom fetch implementation for e.g. testing.

Language Models

You can create models that call the Google Generative AI API using the provider instance. The first argument is the model id, e.g. models/gemini-pro. The models support tool calls and some have multi-modal capabilities.

const model = google('models/gemini-pro');

Google Generative AI models support also some model specific settings that are not part of the standard call settings. You can pass them as an options argument:

const model = google('models/gemini-pro', {
  topK: 0.2,
});

The following optional settings are available for Google Generative AI models:

• topK number

  Optional. The maximum number of tokens to consider when sampling.

  Models use nucleus sampling or combined Top-k and nucleus sampling. Top-k sampling considers the set of topK most probable tokens. Models running with nucleus sampling don't allow topK setting.

• safetySettings Array<{ category: string; threshold: string }>

  Optional. Safety settings for the model.

  • category string

    The category of the safety setting. Can be one of the following:

    • HARM_CATEGORY_HATE_SPEECH
    • HARM_CATEGORY_DANGEROUS_CONTENT
    • HARM_CATEGORY_HARASSMENT
    • HARM_CATEGORY_SEXUALLY_EXPLICIT

  • threshold string

    The threshold of the safety setting. Can be one of the following:

    • HARM_BLOCK_THRESHOLD_UNSPECIFIED
    • BLOCK_LOW_AND_ABOVE
    • BLOCK_MEDIUM_AND_ABOVE
    • BLOCK_ONLY_HIGH
    • BLOCK_NONE

Example

You can use Google Generative AI language models to generate text with the generateText function:

import { google } from '@ai-sdk/google';
import { generateText } from 'ai';

const { text } = await generateText({
  model: google('models/gemini-pro'),
  prompt: 'Write a vegetarian lasagna recipe for 4 people.',
});

Google Generative AI language models can also be used in the streamText, generateObject, streamObject, and streamUI functions (see AI SDK Core and AI SDK RSC).

Model Capabilities